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In this paper we examine Phi-derivable approximations in QED. General theorems tell us that the gauge dependence of the n-loop Phi-derivable approximation shows up at order g^(2n) where g is the coupling constant. We consider the gauge…

High Energy Physics - Phenomenology · Physics 2009-11-10 Jens O. Andersen , Michael Strickland

We derive low-temperature properties of the large-U Hubbard model in two and three dimensions from exact series-expansion results for high temperatures. Convergence problems and limited available information prevent a direct or Pade'-type…

Condensed Matter · Physics 2009-10-22 D. F. B. ten Haaf , P. W. Brouwer , P. J. H. Denteneer , J. M. J. van Leeuwen

In this article, we consider the Euclidean dispersion problems. Let $P=\{p_{1}, p_{2}, \ldots, p_{n}\}$ be a set of $n$ points in $\mathbb{R}^2$. For each point $p \in P$ and $S \subseteq P$, we define $cost_{\gamma}(p,S)$ as the sum of…

Computational Geometry · Computer Science 2021-05-20 Pawan K. Mishra , Gautam K. Das

We present an approximation scheme of the nonperturbative renormalization group that preserves the momentum dependence of correlation functions. This approximation scheme can be seen as a simple improvement of the local potential…

Statistical Mechanics · Physics 2018-05-24 Félix Rose , Nicolas Dupuis

A representation of the Pad\'e approximation of the $Z$-transform of a signal as a resolvent of a tridiagonal matrix $J$ is given. Several formulas for the poles, zeros and residues of the Pad\'e approximation in terms of the matrix $J$ are…

Numerical Analysis · Mathematics 2018-01-18 Luca Perotti , Michal Wojtylak

We present a minimal pole method for analytically continuing matrix-valued imaginary frequency correlation functions to the real axis, enabling precise access to off-diagonal elements and thus improving the interpretation of self-energies…

Strongly Correlated Electrons · Physics 2024-12-16 Lei Zhang , Yang Yu , Emanuel Gull

We study the problem of recovering a globally consistent Euclidean embedding of data, given only a local distance graph and propose a method that optimally represents these distances. The method operates solely on a neighborhood graph…

Machine Learning · Computer Science 2026-05-20 Dimitris Arabadjis

We study the transition of a particle between two points such that the particle takes discrete spatial steps in this transition. We analyze how the sum over histories interpretation of quantum mechanics can be implemented in this scenario.…

Quantum Physics · Physics 2014-03-11 Muhammad Adeel Ajaib

The (conditional or unconditional) distribution of the continuous scan statistic in a one-dimensional Poisson process may be approximated by that of a discrete analogue via time discretization (to be referred to as the discrete…

Probability · Mathematics 2016-02-09 Yi-Ching Yao , Daniel Wei-Chung Miao , Xenos Chang-Shuo Lin

In paper a new definition of reduced Pade approximant and algorithm for its computing is proposed. Our approach is based on the investigation of the kernel structure of the Toeplitz matrix. It is shown that the reduced Pade approximant…

Complex Variables · Mathematics 2011-12-30 Adukov V. M. , Ibryaeva O. L

The use of data-random graphs in statistical testing of spatial patterns is introduced recently. In this approach, a random directed graph is constructed from the data using the relative positions of the points from various classes.…

Statistics Theory · Mathematics 2009-07-01 Elvan Ceyhan

Resummation methods using continued functions are implemented to converge divergent series appearing in perturbation problems related to continuous phase transitions in field theories. In some cases, better convergence properties are…

Statistical Mechanics · Physics 2023-03-09 Venkat Abhignan , R. Sankaranarayanan

Parallel transport is a fundamental tool to perform statistics on Rie-mannian manifolds. Since closed formulae don't exist in general, practitioners often have to resort to numerical schemes. Ladder methods are a popular class of algorithms…

Differential Geometry · Mathematics 2020-07-16 Nicolas Guigui , Xavier Pennec

In this paper, a mixed high order finite difference scheme-Pad\'{e} approximation method is applied to obtain numerical solution of the Riesz fractional advection-dispersion equation. This method is based on the high order finite difference…

Numerical Analysis · Mathematics 2021-05-26 Sohrab Valizadeh , Abdollah Borhanifar

Following the proposal in [1], we study the feasibility to calculate the pion distribution amplitude (DA) from suitably chosen Euclidean correlation functions at large momentum. In our lattice study we employ the novel momentum smearing…

In this note we analyze the use of Pad\'e approximants for downward continuation beyond the radius of convergence of spherical harmonic expansions (SHEs), and for identifying the complex singularities of the gravitational potential. SHEs…

Mathematical Physics · Physics 2026-05-06 Ovidiu Costin , Gerald V. Dunne , Crichton Ogle

We have applied Pade approximants to perturbative QCD calculations of event shape observables in e+e- --> hadrons. We used the exact O(alpha_s^2) prediction and the [0/1] Pade approximant to estimate the O(alpha_s^3) term for 15…

High Energy Physics - Phenomenology · Physics 2009-10-28 P. N. Burrows , T. Abraha , M. Samuel , E. Steinfelds , H. Masuda

In this article we obtain new irrationality measures for values of functions which belong to a certain class of hypergeometric functions including shifted logarithmic functions, binomial functions and shifted exponential functions. We…

Number Theory · Mathematics 2023-10-12 Makoto Kawashima , Anthony Poëls

Most simulation schemes for partial differential equations (PDEs) focus on minimizing a simple error norm of a discretized version of a field. This paper takes a fundamentally different approach; the discretized field is interpreted as data…

Methodology · Statistics 2018-04-18 Reimar H. Leike , Torsten A. Enßlin

This paper is concerned with sampling from probability distributions $\pi$ on $\mathbb{R}^d$ admitting a density of the form $\pi(x) \propto e^{-U(x)}$, where $U(x)=F(x)+G(Kx)$ with $K$ being a linear operator and $G$ being…

Optimization and Control · Mathematics 2024-05-28 Andreas Habring , Martin Holler , Thomas Pock